A fundamental theme in cell biology centers on the structure-function relationships of the macromolecular complexes responsible for cellular events. One goal of structural biology is to obtain a description of these macromolecular machines in their different functional states and in their structural environment. While it is possible to image large macromolecular assemblies, sub-cellular structures and even cells with the aid of electron microscopy, the resolution restrictions of the resulting maps most often precludes direct high-resolution interpretation of these reconstructions. We propose to develop a molecular pattern recognition system for identification and location of molecules in the context of complex structural environments. We will concentrate our efforts on simplified systems of actin- and microtubule-related assemblies. A tight coupling of the development of the methodology with applications to these biologically highly significant assemblies will be employed . This way we will obtain immediate feedback as to how the system performs in practice while providing valuable insight into those systems. For each step, computer-generated model systems will also be used as a tool for development and evaluation. Documentation, tutorials and an easy to-use interface will be developed.